Characteristics of the Internet traffic data flow are studied based on the chaos theory. A phase space that is isometric with the network dynamic system is reconstructed by using the single variable time series of a n...Characteristics of the Internet traffic data flow are studied based on the chaos theory. A phase space that is isometric with the network dynamic system is reconstructed by using the single variable time series of a network flow. Some parameters, such as the correlative dimension and the Lyapunov exponent are calculated, and the chaos characteristic is proved to exist in Internet traffic data flows. A neural network model is construct- ed based on radial basis function （RBF） to forecast actual Internet traffic data flow. Simulation results show that, compared with other forecasts of the forward-feedback neural network, the forecast of the RBF neural network based on the chaos theory has faster learning capacity and higher forecasting accuracy.展开更多
A description of the reliability evaluation of tactical network is given, which reflects not only the non-reliable factors of nodes and links but also the factors of network topological structure. On the basis of this...A description of the reliability evaluation of tactical network is given, which reflects not only the non-reliable factors of nodes and links but also the factors of network topological structure. On the basis of this description, a reliability prediction model and its algorithms are put forward based on the radial basis function neural network (RBFNN) for the tactical network. This model can carry out the non-linear mapping relationship between the network topological structure, the nodes reliabilities, the links reliabilities and the reliability of network. The results of simulation prove the effectiveness of this method in the reliability and the connectivity prediction for tactical network.展开更多
An adaptive backstepping multi-sliding mode approximation variable structure control scheme is proposed for a class of uncertain nonlinear systems.An actuator model with compound nonlinear characteristics is establish...An adaptive backstepping multi-sliding mode approximation variable structure control scheme is proposed for a class of uncertain nonlinear systems.An actuator model with compound nonlinear characteristics is established based on the model decomposition method.The unmodeled dynamic term of the radial basis function neural network approximation system is presented.The Nussbaum gain design technique is utilized to overcome the problem that the control gain is unknown.The adaptive law estimation is used to estimate the upper boundary of neural network approximation and uncertain interference.The adaptive approximate variable structure control effectively weakens the control signal chattering while enhancing the robustness of the controller.Based on the Lyapunov stability theory,the stability of the entire control system is proved.The main advantage of the designed controller is that the compound nonlinear characteristics are considered and solved.Finally,simulation results are given to show the validity of the control scheme.展开更多
This paper is focused on control design for high-precision satellite rendezvous systems.A relative motion model of leader-follower satellites described by relative orbit elements(ROE)is adopted,which has clear geometr...This paper is focused on control design for high-precision satellite rendezvous systems.A relative motion model of leader-follower satellites described by relative orbit elements(ROE)is adopted,which has clear geometric meaning and high accuracy.An improved repetitive control(IRC)scheme is proposed to achieve high-precision position and velocity tracking,which utilizes the advantage of repetitive control to track the signal precisely and conquers the effects of aperiodic disturbances by adding a nonsingular terminal sliding mode(NSTSM)controller.In addition,the nonlinear state error feedback(NLSEF)is used to improve the dynamic performance of repetitive controller and the radial basis function(RBF)neural networks are employed to approximate the unknown nonlinearities.From rigorous Lyapunov analysis,the stability of the whole closed-loop control system is guaranteed.Finally,numerical simulations are carried out to assess the efficiency and demonstrate the advantages of the proposed control scheme.展开更多
This paper presents an integrated guidance and control model for a flexible hypersonic vehicle with terminal angular constraints.The integrated guidance and control model is bounded and the dead-zone input nonlinearit...This paper presents an integrated guidance and control model for a flexible hypersonic vehicle with terminal angular constraints.The integrated guidance and control model is bounded and the dead-zone input nonlinearity is considered in the system dynamics.The line of sight angle,line of sight angle rate,attack angle and pitch rate are involved in the integrated guidance and control system.The controller is designed with a backstepping method,in which a first order filter is employed to avoid the differential explosion.The full tuned radial basis function(RBF)neural network(NN)is used to approximate the system dynamics with robust item coping with the reconstruction errors,the exactitude model requirement is reduced in the controller design.In the last step of backstepping method design,the adaptive control with Nussbaum function is used for the unknown dynamics with a time-varying control gain function.The uniform ultimate boundedness stability of the control system is proved.The simulation results validate the effectiveness of the controller design.展开更多
文摘Characteristics of the Internet traffic data flow are studied based on the chaos theory. A phase space that is isometric with the network dynamic system is reconstructed by using the single variable time series of a network flow. Some parameters, such as the correlative dimension and the Lyapunov exponent are calculated, and the chaos characteristic is proved to exist in Internet traffic data flows. A neural network model is construct- ed based on radial basis function （RBF） to forecast actual Internet traffic data flow. Simulation results show that, compared with other forecasts of the forward-feedback neural network, the forecast of the RBF neural network based on the chaos theory has faster learning capacity and higher forecasting accuracy.
文摘A description of the reliability evaluation of tactical network is given, which reflects not only the non-reliable factors of nodes and links but also the factors of network topological structure. On the basis of this description, a reliability prediction model and its algorithms are put forward based on the radial basis function neural network (RBFNN) for the tactical network. This model can carry out the non-linear mapping relationship between the network topological structure, the nodes reliabilities, the links reliabilities and the reliability of network. The results of simulation prove the effectiveness of this method in the reliability and the connectivity prediction for tactical network.
基金This work was supported by the National Social Science Foundation of China(No.17BGL270).
文摘An adaptive backstepping multi-sliding mode approximation variable structure control scheme is proposed for a class of uncertain nonlinear systems.An actuator model with compound nonlinear characteristics is established based on the model decomposition method.The unmodeled dynamic term of the radial basis function neural network approximation system is presented.The Nussbaum gain design technique is utilized to overcome the problem that the control gain is unknown.The adaptive law estimation is used to estimate the upper boundary of neural network approximation and uncertain interference.The adaptive approximate variable structure control effectively weakens the control signal chattering while enhancing the robustness of the controller.Based on the Lyapunov stability theory,the stability of the entire control system is proved.The main advantage of the designed controller is that the compound nonlinear characteristics are considered and solved.Finally,simulation results are given to show the validity of the control scheme.
基金the National Natural Science Foundation of China(No.61873127)the Key International(Regional)Cooperative Research Projects of the National Natural Science Foundation of China(No.62020106003)。
文摘This paper is focused on control design for high-precision satellite rendezvous systems.A relative motion model of leader-follower satellites described by relative orbit elements(ROE)is adopted,which has clear geometric meaning and high accuracy.An improved repetitive control(IRC)scheme is proposed to achieve high-precision position and velocity tracking,which utilizes the advantage of repetitive control to track the signal precisely and conquers the effects of aperiodic disturbances by adding a nonsingular terminal sliding mode(NSTSM)controller.In addition,the nonlinear state error feedback(NLSEF)is used to improve the dynamic performance of repetitive controller and the radial basis function(RBF)neural networks are employed to approximate the unknown nonlinearities.From rigorous Lyapunov analysis,the stability of the whole closed-loop control system is guaranteed.Finally,numerical simulations are carried out to assess the efficiency and demonstrate the advantages of the proposed control scheme.
文摘This paper presents an integrated guidance and control model for a flexible hypersonic vehicle with terminal angular constraints.The integrated guidance and control model is bounded and the dead-zone input nonlinearity is considered in the system dynamics.The line of sight angle,line of sight angle rate,attack angle and pitch rate are involved in the integrated guidance and control system.The controller is designed with a backstepping method,in which a first order filter is employed to avoid the differential explosion.The full tuned radial basis function(RBF)neural network(NN)is used to approximate the system dynamics with robust item coping with the reconstruction errors,the exactitude model requirement is reduced in the controller design.In the last step of backstepping method design,the adaptive control with Nussbaum function is used for the unknown dynamics with a time-varying control gain function.The uniform ultimate boundedness stability of the control system is proved.The simulation results validate the effectiveness of the controller design.
